定向MWNTs/PMMA的原位聚合制备及耐磨损性

采用原位聚合方法制备了定向碳纳米管/聚甲基丙烯酸甲酯复合材料,并且研究了该复合物的耐磨损性.对定向碳纳米管及其复合物进行了傅立叶红外吸收光谱分析、扫描电镜及光学显微镜观察.采用砝码质量法评价了复合物的耐磨损性.分析结果表明,混酸处理后定向碳纳米管附带了-OH、-COOH基等极性基团.混酸处理后定向碳纳米管束状结构被破坏,定向碳纳米管可以单管形态分散于基体中,碳纳米管表面包覆着PMMA.砝码质量法耐磨损性测试结果表明,定向碳纳米管的加入可提高PMMA复合物的耐磨损性和耐划痕性,当定向碳纳米管用量为0.7%时,复合物的耐磨损性能提升了54%.     

HYDRODYNAMIC STUDIES IN FISCHER-TROPSCH DERIVED WAXES IN A BUBBLE COLUMN

Gas hold-up and Sauter mean bubble diameter measurements were made in a 0.051 m diameter by 3 m long glass bubble column in the system, nitrogen-molten wax, with three different waxes (paraffin wax FT-300, Sasol's Arge wax and Mobil's reactor wax). Paraffin wax has a tendency to foam and gas hold-up is a strong function of gas distributor type, temperature and start-up procedure, whereas the reactor waxes do not foam and are much less affected by these variables, In experiments at 265°C with a 1.85 mm single hole orifice plate distributor the gas hold-ups were nearly the same for all three waxes. However, significant differences in Sauter mean bubble diameters were obtained in experiments with different waxes; FT-300 wax produced the smallest Sauter mean bubble diameters whereas Mobil's reactor wax produced the largest bubbles. Addition of 1-octadecanol and octadecanoic acid (up to 10wt%) to the FT-300 paraffin wax caused an increase in gas hold-up and a delay in the foam break-up in runs at 265°C with the 1.85 mm orifice plate distributor.     

气升式内环流反应器中油滴的分散特性

本文研究了气升式内环流反应器中油滴的分散特性。以对数正态分布密度函数为油滴尺寸的分散模型,导出了油滴的Sauter平均直径解析式。对模型作了实验验证,关联了模型参数。提出了油滴的尺寸分布密度函数和Sauter平均直径的半经验式。结果表明计算值与实验值吻合良好。     

Accelerated electrospark deposition and the wear behavior of coatings

Electrospark deposition (ESD) is a coating process that is featured by low heat input to the substrate. Low coating efficiency and other limitations influence its wider application. The present paper introduces newly designed ESD equipment, by which a higher coating rate can be reached. The relationship among coating thickness, surface roughness, and process parameters such as pulse energy, pulse frequency, and deposition time are presented. Electrospark deposition coating by the new equipment on AISI 1045 steel (with WC-8% Co as electrode) increases the wear resistance by 5 to 8 times. The micromechanism is investigated by scanning electron microscopy observation.     

车轮的热烈和磨损机理与抗热裂耐磨车轮的研制

本文研究了车轮踏面的热裂和磨损机理,结果表明,车轮热裂主要与其含碳量和硬度有关;在使用合成闸瓦时,车轮踏面的磨损率与新形成的“白层”(马氏体)的断裂韧性有关。研制的抗热裂耐磨车轮(55SiMn)取得了明显的运用效果。     

Comparison between Ni-Cr-40vol%TiC wear-resistant plasma sprayed coatings produced from self-propagating high-temperature synthesis and plasma densified powders

Plasma sprayed Ni-Cr-40vol%TiC coatings produced from powders obtained by self-propagating hightemperature synthesis (SHS) and plasma densification (PD) processes are characterized. Chemical composition, microstructure, and mechanical properties, such as microhardness and wear resistance, are evaluated and compared. SHS coatings exhibit good sliding wear performance. The exact stoichiometry of titanium carbide inclusions in the metallic matrix affects the dimension of the crystal lattice parameter and was investigated by examining the shift of x-ray diffraction (XRD) peaks of the TiC. A value of the combined carbon/titanium ratio of about 0.6 was calculated for both powders, thus excluding the influence of the stoichiometry of the carbide inclusions on the wear properties of the coatings.     

Friction and the development of hard alloy surface microstructures during wear

Investigations of wear in sliding friction of WC-Hadfield steel hard alloy against cast tool steel have been carried out in a broad range of velocities and pressure values. Structural and phase composition variations have been revealed. Friction-affected zone was found to be 450 μm in depth. Structural γ → α, γ → transformation regions are located within 100 μm of the surface. These transformations contributed to the total solid solution deformation hardening.     

Wear-resistance and anti-scuffing of multi-arc ion plating molybdenum films

The multi-arc ion plating technology was employed to prepare the molybdenum films with thickness of 3 μm on the AISI 1045 steel. The wear and scuffing tests were carried out on the ball-on-disc tester. AFM and SEM equipped with EDS were adopted to observe and analyze the morphologies and element compositions of surface,cross-section and worn scar of the Mo film. The phase structure was studied by XRD and the bonding strength between Mo film and substrate was measured by scratching tester. The tribological experiments show that the Mo film possesses a good wear-resistance and an excellent anti-scuffing property. The failure mechanism of Mo film under extreme condition is flaking off.     

Modeling of tool wear in drilling by statistical analysis and artificial neural network

The useful life of a cutting tool and its operating conditions largely control the economics of the machining operations. Hence, it is imperative that the condition of the cutting tool, particularly some indication as to when it requires changing, to be monitored. The drilling operation is frequently used as a preliminary step for many operations like boring, reaming and tapping, however, the operation itself is complex and demanding.

Back propagation neural networks were used for detection of drill wear. The neural network consisted of three layers input, hidden and output. Drill size, feed, spindle speed, torque, machining time and thrust force are given as inputs to the ANN and the flank wear was estimated. Drilling experiments with 8 mm drill size were performed by changing the cutting speed and feed at two different levels. The number of neurons in the hidden layer were selected from 1, 2, 3, …, 20. The learning rate was selected as 0.01 and no smoothing factor was used. The estimated values of tool wear were obtained by statistical analysis and by various neural network structures. Comparative analysis has been done between statistical analysis, neural network structures and the actual values of tool wear obtained by experimentation.     

Monitoring of tool wear using measured machining forces and neuro-fuzzy modelling approaches during machining of GFRP composites

The challenges of machining, particularly milling, glass fibre-reinforced polymer (GFRP) composites are their abrasiveness (which lead to excessive tool wear) and susceptible to workpiece damage when improper machining parameters are used. It is imperative that the condition of cutting tool being monitored during the machining process of GFRP composites so as to re-compensating the effect of tool wear on the machined components. Until recently, empirical data on tool wear monitoring of this material during end milling process is still limited in existing literature. Thus, this paper presents the development and evaluation of tool condition monitoring technique using measured machining force data and Adaptive Network-Based Fuzzy Inference Systems during end milling of the GFRP composites. The proposed modelling approaches employ two different data partitioning techniques in improving the predictability of machinability response. Results show that superior predictability of tool wear was observed when using feed force data for both data partitioning techniques. In particular, the ANFIS models were able to match the nonlinear relationship of tool wear and feed force highly effective compared to that of the simple power law of regression trend. This was confirmed through two statistical indices, namely r² and root mean square error (RMSE), performed on training as well as checking datasets.